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Legal and regulatory uncertainty surrounding AI has slowed venture capital investments in recent months. The rapid evolution of AI technology has outpaced regulatory frameworks, resulting in a complex and unpredictable environment for both investors and innovators. The fragmented landscape of policies and laws across different regions, compounded by pending legislation in various jurisdictions, has amplified the challenges faced by investors. Despite some successes for established companies, investors are adopting a more cautious approach, wary of potential regulatory hurdles that could impact the scalability and compliance of AI-driven ventures. This uncertainty is reshaping the dynamics of AI funding and innovation as stakeholders grapple with how to navigate these shifting regulatory currents.
Global Overview
The EU AI Act, which took effect on August 1, 2024, establishes a legal standard for all providers, developers, and deployers of generative AI models within the European Union. As part of the EU’s digital strategy to ensure transparency, safety, and accountability in the development and deployment of AI, the EU has categorized tools into four risk levels: unacceptable, high, limited, and minimal. Generative AI models deemed “high-risk” must adhere to stricter compliance requirements, imposing significant financial and operational burdens on companies involved.
Although the EU AI Act is officially limited to the EU, the cost and complexity associated with retraining large language models make it impractical for companies to create separate AI models for different regions. As a result, the Act has effectively become a de facto global standard. Compliance with the Act’s requirements necessitates expenditure of considerable resources in areas such as development, governance, and human oversight. This increased burden may discourage investors, particularly those backing companies developing “high-risk” generative AI tools.
However, proponents of the EU AI Act contend that the clear regulatory guidelines and transparent risk categories actually enhance investor confidence. By reducing legal uncertainty and setting clear expectations, the Act aims to stabilize the market and offer more predictable conditions for investment in AI-driven innovations. This tradeoff between compliance, costs, and legal certainty may ultimately shape the future trajectory of AI venture capital worldwide.
U.S. Regulatory Patchwork
The United States currently lacks a cohesive federal AI regulatory framework, leaving companies to navigate a fragmented system governed by state laws. This regulatory patchwork complicates compliance efforts for AI startups and investors. Such a patchwork creates several challenges for AI startups and venture capital firms and presents investors with new concerns about the effect of regulations.
First, the inconsistent landscape across states creates significant compliance hurdles. Startups must grapple with a myriad of state regulations that vary in scope, timing, and enforcement. These laws cover a wide range of areas—from election integrity and tax codes to health care, privacy, deepfakes, and intellectual property rights. For example, California’s relatively strict privacy laws place a heavier burden on AI companies compared to more lenient states. This regulatory inconsistency also complicates long-term AI scaling strategies for AI developers, slowing their growth.
Second, regulatory uncertainty complicates the assessment of compliance risks, potentially deterring investment in AI startups that may be subject to sudden regulatory changes. In the absence of statutory law and with no clear legal precedent, issues such as liability for generative AI outputs, data privacy, and content ownership become more complex. As a result, liability agreements and other contractual clauses are subject to heightened scrutiny. These challenges increase compliance costs and complicate due diligence processes for investors, who must evaluate not only a startup’s technology and market potential, but also its ability to navigate a shifting regulatory landscape. As a result, investors may prioritize startups with established compliance strategies or opt to invest in regions with clearer regulatory frameworks.
Third, the uncertainty and variability of state-level AI regulations affects startups with intellectual property in particular. These startups must navigate challenges around proprietary data used in training models and the allocation of intellectual property rights for content generated by AI.
Lastly, the Securities and Exchange Commission has repeatedly cautioned investors about so-called “AI washing,” a practice where companies overstate or inflate their use of AI and its functionalities to appeal to investors, presenting a false image of technological advancement and trustworthiness. While this is not the primary concern for venture capitalists, it adds another layer of risk when evaluating startups, as due diligence now requires deeper investigation into a company’s actual AI capabilities and business model.
Despite these challenges, there is some stabilizing news for investors. Under growing pressure to create a cohesive AI strategy, federal agencies like the National Institute of Standards and Technology have created voluntary guidelines for AI risk management, and President Biden has issued an Executive Order that promotes the safe and secure development of generative AI. However, until the passage of comprehensive federal legislation, AI startups and investors will continue to face regulatory ambiguity in the United States.
Conclusion
The global AI venture capital market is navigating a complex and evolving regulatory landscape. In the EU, the AI Act has established a clear framework that, while imposing significant compliance costs, offers much-needed legal clarity that may bolster investor confidence. Conversely, the United States remains in a state of regulatory fragmentation, with startups and investors grappling with a patchwork of state laws and the absence of comprehensive federal guidance. This uncertainty not only increases compliance risks but also raises concerns around intellectual property, liability, and the true capabilities of AI-driven ventures. Despite these challenges, the growing international focus on AI regulation, such as voluntary guidelines from NIST and executive actions in the United States, signals that the regulatory environment may gradually stabilize. As companies and investors adapt, those able to navigate these hurdles effectively—by prioritizing compliance strategies and focusing on regions with clearer regulations—may be well-positioned to capitalize on the immense potential of AI innovations.
*The views expressed in this article do not represent the views of Santa Clara University.
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